Papers with Code 아카이브

One-Shot Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 1
평가표: 1
보존된 평가 기록: 2

<span style="color:grey; opacity: 0.6">( Image credit: One-Shot Learning for Semantic Segmentation )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Charleshhy/One-shot-Human-Parsing

공식 코드

Progressive One-shot Human Parsing

https://github.com/LEw1sin/Uncertainty-Ensemble

공식 코드

Memory-based Ensemble Learning in CMR Semantic Segmentation

https://github.com/RPL-CS-UCL/UCL-AffCorrs

공식 코드

One-Shot Transfer of Affordance Regions? AffCorrs!

https://github.com/Wi-sc/BriNet

공식 코드

BriNet: Towards Bridging the Intra-class and Inter-class Gaps in One-Shot Segmentation

https://github.com/Zch0414/P2SAM

공식 코드

Part-aware Personalized Segment Anything Model for Patient-Specific Segmentation

https://github.com/antoinehabis/Deep-ContourFlow

공식 코드

Deep ContourFlow: Advancing Active Contours with Deep Learning

https://github.com/avm-debatr/bagganhq

공식 코드

Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN Images

https://github.com/avm-debatr/ganecdotes

공식 코드

Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN Images

https://github.com/boschresearch/one-shot-synthesis

공식 코드

One-Shot Synthesis of Images and Segmentation Masks

https://github.com/d-iceice/one-shot-irsts

공식 코드

One Shot is Enough for Sequential Infrared Small Target Segmentation

https://github.com/fiy2w/mri_seq2seq

공식 코드

Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRI

https://github.com/hsiangyuzhao/adler

공식 코드

AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation

https://github.com/jinxlv/one-shot-segmentation-via-ist

공식 코드

Robust One-shot Segmentation of Brain Tissues via Image-aligned Style Transformation

https://github.com/liuwan0208/one-shot-extensive-data-augmentation

공식 코드

One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation

https://github.com/lwhyc/oneshot_weaklyseg

공식 코드

One-shot Weakly-Supervised Segmentation in Medical Images

https://github.com/lzzcd001/OSLSM

공식 코드

One-Shot Learning for Semantic Segmentation

https://github.com/menglcool/segic

공식 코드

SEGIC: Unleashing the Emergent Correspondence for In-Context Segmentation

https://github.com/mengweiren/longitudinal-representation-learning

공식 코드

Local Spatiotemporal Representation Learning for Longitudinally-consistent Neuroimage Analysis

https://github.com/michaelisc/cluttered-omniglot

공식 코드

One-Shot Segmentation in Clutter

https://github.com/rudylyh/CTN_data

공식 코드

Contour Transformer Network for One-shot Segmentation of Anatomical Structures

https://github.com/timojl/clipseg

공식 코드

Image Segmentation Using Text and Image Prompts

https://github.com/usagisukisuki/oneshot-part-cellsegmentation

공식 코드

One-shot and Partially-Supervised Cell Image Segmentation Using Small Visual Prompt

https://github.com/zaplm/dc-sam

공식 코드

DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency

https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/clipseg

Image Segmentation Using Text and Image Prompts

https://github.com/MindSpore-scientific/code-7/tree/main/ImageGPT

Image Segmentation Using Text and Image Prompts

https://github.com/RogerQi/pascal-5i

One-Shot Learning for Semantic Segmentation

https://github.com/casia-iva-lab/fastsam

Image Segmentation Using Text and Image Prompts

https://github.com/chunbolang/DCP

One-Shot Learning for Semantic Segmentation

https://github.com/huggingface/transformers

Image Segmentation Using Text and Image Prompts

https://github.com/ml4ai/mliis

One-Shot Learning for Semantic Segmentation

https://github.com/openrobotlab/ov_parts

Image Segmentation Using Text and Image Prompts

https://github.com/vamsirk/FewShotLearning

One-Shot Learning for Semantic Segmentation

https://github.com/vamsirk/OneShotSemanticSegmentation

One-Shot Learning for Semantic Segmentation

https://github.com/woaixuexixuexi/PSANet

One-Shot Learning for Semantic Segmentation

https://github.com/zwzheng98/qclnet

One-Shot Learning for Semantic Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.